Application of machine learning in identifying risk factors for low APGAR scores
This study underscores the importance of incorporating machine learning approaches in obstetric care to understand better and mitigate the risk factors associated with adverse neonatal outcomes, particularly low APGAR scores. The results provide a foundation for developing targeted interventions and improving prenatal care practices.
Authors
- Ishag Adam (ORCID: https://orcid.org/0000-0001-5031-7741)
- Haifa F. Alhasson (ORCID: https://orcid.org/0000-0002-6503-2826)
- Shuaa S. Alharbi (ORCID: https://orcid.org/0000-0003-2121-0296)
- Nagat B. Elhag (ORCID: https://orcid.org/0009-0006-9159-479X)
Institutions
- Qassim University (SA)
- Buraydah Colleges (SA)
Publication Details
- Journal
- BMC Pregnancy and Childbirth
- Published
- 2025-05-08
- DOI
- https://doi.org/10.1186/s12884-025-07677-y
- Citations
- 1
- Primary Topic
- Cardiac Imaging and Diagnostics
- Type
- article
- Field-Weighted Citation Impact
- 1.36
Funders
- Qassim University